Proving a Basis for a Vector Space

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SUMMARY

The discussion focuses on proving a basis for the vector space R^3 using linear transformations and matrix representations. Participants emphasize the importance of row reduction techniques, specifically transforming matrices like [(1,5);(1,6)] to the reduced row echelon form [(1,0);(0,1)]. The method for finding the matrix representing a linear transformation involves applying the transformation to each basis vector and expressing the results as linear combinations of the basis vectors. Additionally, the discussion highlights two approaches for solving problems related to change of basis matrices.

PREREQUISITES
  • Understanding of linear transformations and their matrix representations.
  • Familiarity with row reduction techniques in linear algebra.
  • Knowledge of basis vectors and linear combinations.
  • Experience with change of basis matrices in vector spaces.
NEXT STEPS
  • Study the process of row reducing matrices to understand linear independence.
  • Learn how to construct and utilize change of basis matrices in vector spaces.
  • Explore the application of linear transformations to different basis vectors.
  • Investigate the properties of linear combinations in the context of vector spaces.
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Students and educators in linear algebra, mathematicians focusing on vector spaces, and anyone involved in computational mathematics or applied linear transformations.

shaon0
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Homework Statement


See Attachment.

The Attempt at a Solution


For the first two questions, I know I have to sub in values for a and b. But, I'm not sure what the output matrix is.
The 3rd q, to prove B is Basis for R^3. I just have to row reduce [(1,5);(1,6)] to get [(1,0);(0,1)] right? But like before, I don't know how to do b).

Any help is appreciated.
 

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To find the matrix representing a given linear transformation, in a given ordered basis, apply the linear transformation to each basis vector in turn. Write the result as a linear combination of the basis vectors. The coefficients give the columns of the matrix.

For example, [itex]f(x^2)= (x^2)'= 2x= 2(1+ x)- 2(1)= -2(1)+ 2(1+ x)+ 0(x^2)[/itex]. Since the basis is [itex]\{1, 1+ x, x^2\}[/itex], in that order, the third column of the matrix would be
[tex]\begin{bmatrix}-2 \\ 2 \\ 0\end{bmatrix}[/tex]


For 6(b) there are two different ways to do this. The most direct would be to use the matrix, as given, to determine [itex]T\left(\begin{array}{c} 1 \\ 5\end{array}\right)[/itex] and [itex]T\left(\begin{array}{c}1 \\ 6\end{array}\right)[/itex] and then write the results as linear combinations of those new basis vectors. Another would be to construct the "change of basis" matrix and multiply by that.
 
HallsofIvy said:
To find the matrix representing a given linear transformation, in a given ordered basis, apply the linear transformation to each basis vector in turn. Write the result as a linear combination of the basis vectors. The coefficients give the columns of the matrix.

For example, [itex]f(x^2)= (x^2)'= 2x= 2(1+ x)- 2(1)= -2(1)+ 2(1+ x)+ 0(x^2)[/itex]. Since the basis is [itex]\{1, 1+ x, x^2\}[/itex], in that order, the third column of the matrix would be
[tex]\begin{bmatrix}-2 \\ 2 \\ 0\end{bmatrix}[/tex] For 6(b) there are two different ways to do this. The most direct would be to use the matrix, as given, to determine [itex]T\left(\begin{array}{c} 1 \\ 5\end{array}\right)[/itex] and [itex]T\left(\begin{array}{c}1 \\ 6\end{array}\right)[/itex] and then write the results as linear combinations of those new basis vectors. Another would be to construct the "change of basis" matrix and multiply by that.
Thanks HallsOfIvy; I still don't understand how to do the other two though. My approach is sub in values for a and b which correspond to the co-effs. of the given basis. Then assemble a matrix from them. Eg: f[(5,0);(1,3)]=[(1,1);(2;-1)] which gives me [(-17,4);(15,-3)] for c).
 
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